Emerging Technologies in Digitalisation

  • Unterricht

    Details

    Fakultät Wirtschafts- und Sozialwissenschaftliche Fakultät
    Bereich Wirtschaftsinformatik
    Code UE-EIG.00169
    Sprachen Englisch
    Art der Unterrichtseinheit Vorlesung
    Kursus Master
    Semester SP-2021

    Zeitplan und Räume

    Vorlesungszeiten Mittwoch 09:15 - 12:00, Wöchentlich
    Stunden pro Woche 3

    Unterricht

    Verantwortliche
    Dozenten-innen
    Assistenten
    Beschreibung

    In this course we will investigate emgerging technologies in the area of digitalization of enterprises such as blockchains and smart contracts, augmented and virtual reality, data warehouses, machine learning platforms, semantic technologies and others. The concrete range of technologies will be announced at the beginning of the course. The goal is to conduct explorative research on the characteristics of these technologies and the resulting opportunities for business applications.

    For this purpose, small projects will be conducted in teams for analyzing particular usage scenarios for the technologies, designing according solutions using techniques of conceptual modeling and implementing them in the form of prototypes. Following lectures for introducing the foundations of the technologies, students will set up their own projects and regularly report upon the advancement in the projects in the form of common presentations. At the end, final presentations of the projects including working prototypes and the submission of a seminal report based on scientific standards are required. For the implementation of the prototypes it is necessary to dispose of programming knowledge, e.g. in Java, Node.js, or Python.

    Moodle Link

    Lernziele

    The goal of this course is to get a fundamental understanding of common technologies in the context of digitalization of enterprises and being able to create according software applications. Further, the writing of seminal papers is trained for preparing students to conduct their own research as e.g. required for master and doctoral theses.

    Soft Skills
    Nein
    ausserhalb des Bereichs
    Nein
    BeNeFri
    Ja
    Mobilität
    Ja
    UniPop
    Nein

    Dokument

    Bibliographie

    * Narayanan, Arvind, Clark, Jeremy (2017): Bitcoin's Academic
    Pedigree. ACMQueue, Volume 15, issue 4.
    https://queue.acm.org/detail.cfm?id=3136559

    * Antonopoulos, Andreas M., Wood, Gavin (2018): Mastering Ethereum.
    O’Reilly. https://github.com/ethereumbook/ethereumbook

    * Hyperledger Fabric (2020): Documentation.
    https://hyperledger-fabric.readthedocs.io/en/release-2.2/whatis.html

    * Three.js Documentation (2020): https://threejs.org/docs/

    * KNIME Analytics Documentation (2020): https://docs.knime.com/

    * RapidMiner Educational License Program (2020):
    https://rapidminer.com/educational-program/

    * R Platform Manuals (2020): https://cran.r-project.org/manuals.html

    * Protégé Documentation (2020):
    https://protegewiki.stanford.edu/wiki/Main_Page

  • Einzeltermine und Räume
    Datum Zeit Art der Unterrichtseinheit Ort
    24.02.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    03.03.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    10.03.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    17.03.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    24.03.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    31.03.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    14.04.2021 09:15 - 12:00 Kurs PER 21, Raum F207
    21.04.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    28.04.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    05.05.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    12.05.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    19.05.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    26.05.2021 09:15 - 12:00 Kurs PER 21, Raum B207
    02.06.2021 09:15 - 12:00 Kurs PER 21, Raum B207
  • Leistungskontrolle

    Schriftliche Prüfung - SP-2021, Wiederholungssession 2021

    Bewertungsmodus Nach Note
    Beschreibung

    Exam lenght: 90 minutes

    Only as a retake exam

    Fortlaufende Evaluation - SP-2021, Sommersession 2021

    Bewertungsmodus Nach Note
  • Zuordnung
    Zählt für die folgenden Studienpläne:
    Business Communication - Wirtschaftsinformatik 90 ECTS [MA]
    Version: 2020/SA_V01
    Kurse - 60 ECTS > Optionsgruppe > Wirtschaftsinformatik > Kurse > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization

    Data Analytics 30 [MA]
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization

    MSc in Informatik (BeNeFri)
    Version: 2010_2/V_02
    MSc in Informatik (BeNeFri), Vorlesungen, Seminare und Masterarbeit > T5: Information Systems and Decision Support

    Masternebenfach: Wirtschaftsinformatik 30 [MA]
    Version: 2020/SA_V01
    Kurse > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization

    Wirtschaftsinformatik 90 ECTS [MA] - SA/2019
    Version: 2019/SA_V01
    Kurse - min. 45 ECTS > Module Wirtschaftsinformatik/Informatik > TMD: Technologies and Modelling for Digitalization
    Kurse - min. 45 ECTS > Module Wirtschaftsinformatik - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization

    Wirtschaftsinformatik 90 ECTS [MA] - SA/2020
    Version: 2020/SA-v01
    Kurse - min. 45 ECTS > Module Wirtschaftsinformatik - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
    Kurse - min. 45 ECTS > Module Wirtschaftsinformatik/Informatik > TMD: Technologies and Modelling for Digitalization